ProLIF Protein-Protein Interface Fingerprinting Skill
SkillDev toolsProLIF protein-protein trajectory analysis skill for interface interaction fingerprints and stability profiling.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the ProLIF Protein-Protein Interface Fingerprinting Skill skill
What this skill tells your AI
The instructions your AI receives, as published by internscience/molclaw in skills/L1_tools/molclaw-prolif-protein-protein/SKILL.md and read by ahel’s review.
Note:
- Local files are not directly accessible by the server. Please upload them to the server using
molclaw-file-transferbefore execution. - For PDB file inputs, it is recommended to preprocess them using
molclaw-pdbfixerbefore execution. - Please refer to skill
molclaw-scp-serverto complete tool invocation.
[!NOTE] Local files are not directly accessible by the server. Please upload them to the server using
molclaw-file-transferbefore execution. For PDB file inputs, it is recommended to preprocess them usingmolclaw-pdbfixerbefore execution.
Task Description
Analyze protein-protein interaction trajectories and generate interface interaction fingerprints. Use this skill to evaluate interface stability and identify key residue contributions across simulation.
Routing note: This tool is the primary choice for protein-protein trajectory interface profiling (multi-frame analysis). For single-structure protein-protein interface analysis, use
molclaw-interaction-visualizerin protein mode instead — it produces interface heatmaps, network diagrams, and decision-ready JSON.
Input Source Mapping
| Parameter | Source Guidance |
|---|---|
topology_path | System topology from MD tools: e.g., protein_openmm_md, prepare_protein_md, goca_pipeline |
trajectory_path | Trajectory from the same MD tools, containing dynamic information for both protein chains |
selection_a | User-defined selection string for protein chain A, for example segid A or protein and chainid A |
selection_b | User-defined selection string for protein chain B, for example segid B or protein and chainid B |
Usage
Tool: prolif_protein_protein
Analyze a protein-protein trajectory and return interaction fingerprints or counts with summary metrics.
Args:
topology_path (str): Path to the system topology file.
trajectory_path (str): Path to the trajectory file.
selection_a (str): Selection string for partner A.
selection_b (str): Selection string for partner B.
interactions (List[str]|None): Optional interaction types to compute.
count (bool): If True, compute interaction counts instead of fingerprints. Default: False.
vicinity_cutoff (float|None): Optional distance cutoff for vicinity interactions.
params_json (str|None): Optional JSON parameter file path for ProLIF interaction settings.
start (int|None): Optional start frame index.
stop (int|None): Optional stop frame index (exclusive).
step (int|None): Optional frame stride.
Return:
status (str): 'success' or 'error'.
msg (str): Human-readable summary or error message.
command (str): The executed command label ('protein-protein').
output_dir (str|None): Run-specific directory under tool_result/prolif_result.
output_file (str|None): Path to the generated CSV file.
n_frames (int|None): Number of processed frames.
n_interactions (int|None): Number of interaction columns in output.
frequent_interactions (List[dict]|None): High-frequency interactions (>30%) with keys 'interaction' and 'frequency'.
result_summary (dict|None): Full summary dictionary from the wrapper.
How To Use prolif_protein_protein
response = await client.session.call_tool(
"prolif_protein_protein",
arguments={
"topology_path": "relative/path/to/system.prmtop",
"trajectory_path": "relative/path/to/md.nc",
"selection_a": "segid A",
"selection_b": "segid B",
"start": 0,
"step": 10
}
)
result = client.parse_result(response)
key_output = result["output_file"]
Example Parameter Sets
# 1) Main mode
{
"topology_path": "relative/path/to/system.prmtop",
"trajectory_path": "relative/path/to/md.nc",
"selection_a": "segid A",
"selection_b": "segid B",
"start": 0,
"step": 10
}
# 2) Variant mode
{
"topology_path": "relative/path/to/system.prmtop",
"trajectory_path": "relative/path/to/md.nc",
"selection_a": "protein and chainid A",
"selection_b": "protein and chainid B",
"count": True,
"vicinity_cutoff": 3.5,
"stop": 200
}
Signals
- GitHub stars
- 33
- Forks
- 3
- Last commit
- Aug 2026
Advanced
- Catalog kind
- skill
- Gateway key
molclaw-prolif-protein-protein- Source
- github.com/internscience/molclaw